MSci (Hons) Computer Science (with Industrial Experience) · Lancaster UniversityIntegrated Master's degree · 4 years
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Lancaster University · Undergraduate

MSci (Hons) Computer Science (with Industrial Experience) Integrated Master's degree at Lancaster University

MSci (Hons) Computer Science (with Industrial Experience) at Lancaster University is recognised as a UK degree-awarding body, with degrees that hold national recognition.

MSci (Hons)
Award
4
Years
Full-time
Study mode
90%
in work/study (15m)

About this course

Find out more about studying Computer Science (with Industrial Experience) MSci Hons (G404) at Lancaster University From the provider’s course page.

MSci (Hons) Computer Science (with Industrial Experience) is an Integrated Master's degree (MSci (Hons)) at Lancaster University, based in Bailrigg Campus, Lancaster. It runs 4 years, studied full-time.

For Computer science graduates from this provider, 90% were in work or further study 15 months after graduating, 90% in highly skilled roles, typical earnings around £33,500. (HESA Graduate Outcomes / LEO, via Discover Uni.)

For the typical curriculum, specialisations, career paths and graduate earnings for Computer Science, see the sections below.

Course evidence score

The arithmetic mean of the official measures available for this course: NSS satisfaction, graduate activity and continuation.

8.5
/ 10
Excellent
3 of 3 official measures
Student satisfaction
What students say in the National Student Survey
Strong69

Published threshold met NSS publication requires sufficient responses; small differences are not a rank. NSS mean of 7 published themes (Discover Uni snapshot 2026-06-21)

Graduate outcomes
In work or further study 15 months after graduating
Exceptional90

Moderate evidence Published sample: 40; avoid reading small differences as meaningful. Cohort 2021-23. Graduate Outcomes work or further study 90% (2022-23; Discover Uni snapshot 2026-06-21)

Continuation
Students who continue past their first year
Exceptional95

Published threshold met Discover Uni suppresses continuation data below its publication threshold. Cohort 2022-23. Continuation 95% (2022-23; Discover Uni snapshot 2026-06-21)

Curriculum & modules

Real modules published for this course, grouped only where the source gives a year, stage or level.

Year 1 8 modules
  • Designing Software SystemsCore
    Module details

    Software development is a collaborative and creative process. You will investigate the processes, tools, techniques, and notations required to successfully engage in the development of commercial grade software. Focusing on the key non-functional parameters of software reuse, scalability, maintainability and extensibility, you will explore the benefits brought by the rigour associated with object-oriented, strongly typed languages (such as Java). You will practice the concepts of composition, inheritance, polymorphism, interfaces, and traits and the commonly employed design patterns that they enable. You will also study the processes and notations associated with defining the relationships a

  • Digital SystemsCore
    Module details

    The creation of the microprocessor revolutionised global innovation and creativity. Without such hardware there would be no laptops, no smartphones, no tablets. Life changing technologies, from MRI scanners to the internet, would simply not exist. This module introduces the field of digital systems, the engineering principles upon which all contemporary computer systems are based. You will study the elements that work together to form the architecture of digital computers, including computer processors, memory, data storage and input/output. You will also unearth the ways in which these are enabled by digital logic, where George Boole’s theory of a binary based algebra meets electronics. Dis

  • Fundamentals of Computer ScienceCore
    Module details

    Computing and data control many critical elements of modern society. It’s vital that there is a strong theoretical foundation to computer science. We begin by examining the hard questions at the centre of computer science. You will cover the fundamentals in logic, sets, and mathematics of vectors, matrices and linear algebra and their practical applications in software, such as computer graphics. Algorithms, abstract data types, and analysis of algorithms is introduced to allow you to make reasonable decisions about the design of your programs. Finally, you will get the chance to investigate the principles of data science to select, process and analyse data, and examine the way programs and

  • Software DevelopmentCore
    Module details

    Software forms a central aspect of our lives. From the applications we run on our phones to satellites in space, all modern technology is enabled by software. In this module, you will focus on Software Development, the processes and skills associated with designing and constructing computer programs. Designed with your needs in mind, whether you have previous experience in computing or not, we adapt to ensure you gain the contemporary knowledge, skills and techniques needed to develop high-quality computer software. This includes a thorough treatment of the principles of computer programming and how these principles can be applied using a range of contemporary and established languages such

  • Contemporary Topics in ComputingOptional
    Module details

    Computer science is a discipline that continues to innovate at a remarkable pace, changing nearly every aspect of modern life as it does so. We introduce you to a range of special topics that reflect the latest aspects of computing. Examples include physical computing, soft robotics, applications of AI, computer science innovation and tech entrepreneurship. The exact topics explored changes year by year to ensure you cover ideas at the cutting-edge of contemporary computer science thinking. Guest speakers will help stimulate debate and topics will include lectures and lab sessions to provide a blend of theoretical and practical skills. At the end of the module, you will understand multiple e

  • DevOpsOptional
    Module details

    This module seeks to extend traditional development skills by covering core issues in computing operations. Developing expertise in this area is increasingly important as many software companies embrace the concept of DevOps, in which development and operations are brought together to ensure a unified approach to designing, developing, delivering and supporting complex software systems. You will gain an understanding of the key areas in computer operations, including systems administration, deployment and software evolution, while practical labs will be used to teach emerging DevOps tools.

  • Matrices and CalculusOptional
    Module details

    Interested in how mathematicians build theories from basic concepts to complex ideas, like eigenvalues and integration? Journey from polynomial operations to matrices and calculus through this module. Starting with polynomials and mathematical induction, you will learn fundamental proof techniques. You will explore matrices, arrays of numbers encoding simultaneous linear equations, and their geometric transformations, which are essential in linear algebra. Eigenvalues and eigenvectors, which characterise these transformations, will be introduced, highlighting their role in applications including population growth and Google's page rankings. Next, we will reintroduce you to calculus, from its

  • Probability and StatisticsOptional
    Module details

    An introduction to the mathematical and computational toolsets for modelling the randomness of the world. You will learn about probability, the language used to describe random fluctuations, statistics and the mathematical techniques used to extract meaning from data. You will explore how computing tools can be used to solve challenges in scientific research, artificial intelligence, machine learning and data science. You will develop the axiomatic theory of probability, discover the theory and uses of random variables and investigate how theory matches intuitions about the real-world. You will then dive into statistical inference, learning to select appropriate probability models to describ

Year 2 13 modules
  • Computer Science Group ProjectCore
    Module details

    During this module, you will undertake a project from conception to completion, working to meet a client brief and applying the concepts and skills gained so far in a practical setting. Working in a group, develop your skills in prototyping, project planning, management, design, user evaluation and testing strategies. Your team will be expected to deliver reports, code and demonstrate a working system by the project’s conclusion. The topics explored differ year to year. Past examples include desktop application development, game programming and computer graphics. Throughout, you will take part in weekly workshops, a space to where you can work as a group and receive support and guidance. Lec

  • HCI: Designing for PeopleCore
    Module details

    Human-computer interaction (HCI) is concerned with all aspects of designing, building, evaluating, and studying systems that involve human interaction. From a computing perspective, the focus is on enabling interaction through user interfaces and on creating interactive systems that provide a positive user experience. The module introduces you to the foundations of HCI, where you delve into human behaviour, technologies for interaction and human-centred design. You will review human perception, cognition and action, and relate these to design principles and guidelines. As part of this, you will discuss different paradigms of user interface and key technologies such as pointing. You will then

  • Networks and SystemsCore
    Module details

    Investigate the deeper concepts that underpin computer networking and operating systems. You will explore the role, operation, and design rationale of the IP protocol suite that enables the global internet. Taking a top-down approach, discover how protocols such as HTTP, DNS, and TCP/IP operate on a fundamental level, and the metrics and tools we use to evaluate the performance of computer networks. Core operating system concepts will be built upon and expanded to develop an comprehensive understanding of the components of an operating system such as the kernel, scheduling, access control, memory management and file systems. Using simulators, you will explore first-hand how data is efficient

  • Secure Data and SystemsCore
    Module details

    We introduce the foundational principles of systems security, focusing on Confidentiality, Integrity and Availability; and Authentication, Authorisation and Accountability (AAA). You will explore access control models, security policies and the mechanisms that underpin secure system design. You will learn about the main categories of cryptosystems (e.g. symmetric, asymmetric) highlighting their practical applications and limitations in real-world contexts. We also investigate common system vulnerabilities and the tools and techniques used by attackers. Through structured, hands-on lab sessions, you will develop practical skills in identifying, analysing and mitigating threats.

  • Artificial IntelligenceOptional
    Module details

    Delve into the key principles of artificial intelligence (AI), touching on the core concepts and philosophy of AI and discussing its presence and ethical challenges in the modern world. Throughout, you will unearth the underlying principles of search spaces, knowledge representation and inference logic that form the core of rule-based systems, before learning the principles of machine learning, clustering, classification, linear regression and neural networks. From this, you will have the grounding necessary to progress to modules in topics such as machine learning, computer vision, and NLP. You will also gain a deeper understanding of computational problem solving, exploring the very nature

  • Concurrent and Parallel SystemsOptional
    Module details

    Computer architecture has now reached a critical juncture where we are witnessing a steep change in computer performance, not due to the increased performance of individual processors, but through the inclusion of many, sometimes even thousands, of processor cores in a single computer. This requires new ways of thinking about these concurrent systems, and operating systems in general. Dive into the theory and practical application of advanced operating systems (OS) and associated hardware concepts. Through a combination of lab exercises and lectures, you will investigate the ways that modern operating systems are optimised to extract the maximum performance and efficiency from 21st century c

  • Extended RealityOptional
    Module details

    Extended reality (XR) refers to the interactive technologies that blend virtual and physical worlds into a hybrid environment or immersive experience. The technology is based on multi-modal platforms that integrate the use of widespread, wearable computing. In this module, you will explore different uses of extended reality within the reality-virtuality continuum and identify the needs and means of augmenting human senses. You will take an applied approach to the design, implementation, deployment, and evaluation of systems that are used to create an XR environment and deliver an immersive experience. To do this, you will study the latest trends in research, emerging technologies, and novel

  • Internet ApplicationsOptional
    Module details

    The internet and the world wide web have now pervaded every aspect of our lives, from ecommerce and entertainment to logistics and social media. Increasingly, application software is no longer written for specific devices, but for internet web browsers. The internet has replaced operating systems as the de-facto platform for application development, making an already global phenomenon now commonplace. This module explores the various approaches to the development of internet applications, investigating both the client and server-sides, and discussing the trade-off of performance, scalability, privacy and trust associated with these approaches. You will review the role of ‘cloud infrastructur

  • AlgorithmsOptional
    Module details

    Build upon the foundations of algorithms and their complexity to develop a deeper understanding of algorithmic approaches to computational problem solving. Explore computational complexity theory, which allows us to consider the very nature of computability - including non-deterministic polynomial (NP) complexity classes such as NP-hard, NP-complete and the classes of problems which cannot be solved. You will be introduced to classical approaches to problem solving such as divide and conquer, recursion, and parallel approaches, emphasising their relative benefits and weaknesses to different classes of problem. You will also study advanced data structures in depth, such as tries, heaps, suffi

  • Applied Security MethodsOptional
    Module details

    We explore a practical and applied aspect of cyber security: penetration testing. You will learn common approaches and tools that attackers use to undermine the security of digital systems and gain first-hand experience of the weaknesses that can be present in real-world systems through guided work in highly controlled, small-group practical labs. The module will wrap the technical and theoretical aspects within the llegal, regulatory and ethical frameworks for the appropriate application of ethical penetration testing.

  • Data EngineeringOptional
    Module details

    This module provides a practical and theoretical background to the design, implementation, and use of database management systems, both for data designers and application developers. It incorporates consideration of information quality and security in the design, development, and use of database systems. You will be introduced to a brief history of database management systems, Entity-Relationship Models, the relational model and the data normalisation process, and alternative schema definitions, NoSQL and object-oriented data models, big data, as well as transaction processing and concurrency control. The module embeds practical access and retrieval considerations and how to interact with da

  • Operating SystemsOptional
    Module details

    Take a deep dive into the theory and practical application of advanced operating systems (OS) and associated hardware concepts. Through a combination of lab exercises and lectures, investigate the ways that modern operating systems are optimised to extract the maximum performance and efficiency from 21st century computer hardware. Study how the fundamental concept of virtualisation enables safe, efficient and fair sharing of memory and processor resources across multiple applications and services. Investigate the structure, operation and scalability of OS subsystems, such as memory allocators and file systems, as well as discuss the performance implications of operating systems and discover

  • Sustainable ComputingOptional
    Module details

    Computing plays a pivotal role in addressing growing energy costs, greenhouse emissions and the climate crisis. Whilst we can use computing and its associated digital technologies to shape a greener society (as well as create more energy-efficient software and hardware), there exist important trade-offs with respect to economic cost, engineering effort and environmental impact. You will explore key concepts associated with creating sustainable computing, spanning from how a processor uses electricity to how computers shape a greener economy and society. You will study the methods to create more energy-efficient code, energy-aware device mechanisms, as well as the benefits and drawbacks of co

Year 3 15 modules
  • Third Year Project (Computer Science)Core
    Module details

    You will undertake a substantial individual project, typically involving the principled design, implementation, and evaluation of a substantial piece of software, experimental study, or theoretical work. To assist in this, an academic will provide a large range of project ideas covering the breadth of our School’s expertise, which you will rank by level of interest before being allocated to a supervisor. You will also have the opportunity to write your own project idea and find a supervisor that would like to support you, and projects can be carried out in collaboration with an external partner, such as a company. Throughout the project, you will be expected to attend regular one-to-one meet

  • Advanced NetworkingOptional
    Module details

    Computer networks have experienced an exponential growth in traffic and size since the early days of the internet. Packet network technologies underpin every aspect of our daily life. On this module, you will investigate how network technologies have evolved to cope with increasing demands, the architecture of devices, and protocols that facilitate end-to-end connectivity, while allowing control of connectivity properties like bandwidth and latency. You will explore cutting-edge research and industry perspectives regarding the challenges that face production network technologies, such as performance and security, and speculate on the future direction networking will take. Practical sessions

  • Advanced ProgrammingOptional
    Module details

    Dive into alternative programming language paradigms, beyond imperative and object-oriented programming. Emphasis is placed on functional programming languages and their unique constraints and features, such as more expressive type systems, immutability, pure functions and side-effects, lambdas, higher order functions, currying, map/reduce and pattern matching. You will also explore why functional languages bring about increased reliability and scalability and how they are now experiencing a resurgence within the software industry. Through hands-on laboratory sessions, you will learn a functional programming language, such as Haskell, and see how functional programming concepts are being int

  • Computer Science EducationOptional
    Module details

    Learn how to teach computer science as a discipline, including organising engaging activities that address the digital skills gap, and inspiring new computer scientists. Through practical sessions, you will build a foundational understanding of computing pedagogy, learning to recognise how learners study computer science and arrange teaching to respond to their needs. You’ll explore the instruments and methods for effective teaching practices, considering UK and global contexts, and the differences within primary, secondary, and higher education. The importance of equality, diversity, and inclusion (EDI), ethics, safeguarding and integrity considerations in education will be highlighted thro

  • Computer VisionOptional
    Module details

    Computer vision is a branch of artificial intelligence which aims to build computer-based systems that can interpret and draw meaning from digital images. This module digs into the fundamentals of image formation, information relating to the human visual system, and image interpretation methodologies including convolution, edge detection and feature extraction, and comparison. You will tackle key problems in current research, including semantic segmentation, object detection and three-dimensional image interpretation. You will cover a range of approaches, from low-level image processing to convolutional neural networks. At the end of the module, you will be equipped to construct software com

  • Digital HealthOptional
    Module details

    Digital Health explores the utilisation of digital technologies in healthcare. These technologies have an ever-growing role to play in transforming health and care delivery and supporting individuals to improve their health. Discover the practical applications, implications, and how to enable technologies of digital health. You will survey sensor technologies that permit remote and automated patient monitoring and study the technologies and processes that enable patient-driven healthcare. You will also investigate the structure of health data in electronic health records and methods for the evaluation of digital health solutions. Alongside these applied topics, you’ll also learn about data g

  • Distributed SystemsOptional
    Module details

    Large scale distributed computing systems are now commonplace, implemented using ‘cloud infrastructures’ where computing and storage resources are pooled into data centres around the globe. In scientific terms, these are examples of distributed systems. Learn about the fundamental principles that underpin modern distributed systems, the abstractions on which they are based, and their characteristics. Emphasis is placed on the scalability and fault-tolerance of these systems, and you will dive into the commonly used frameworks for distributed systems, such as Google’s infrastructure, and highly distributed peer to peer approaches. Small group practical labs reinforce theory through hands-on e

  • Embedded SystemsOptional
    Module details

    Understand the challenges associated with developing firmware for embedded systems, which is increasingly common in everyday appliances due to a rise in cyber-physical systems, smart cities, and the Internet of Things. You will engage with relevant hardware and low-level programming as you study the architecture of microcontrollers (highly specialised, resource constrained computer processors that power embedded systems). Building on this, you will then learn about the state-of-the-art software development processes that facilitate the writing of highly efficient code for such devices. You’ll become familiar with industry standard protocols and techniques for integrating peripherals with mic

  • Languages and CompilationOptional
    Module details

    All programming languages are based on theoretical principles of formal language theory. In this module, you dive deep into formal languages representation and grammars, and how they relate to programming language compilers and interpreters. You will study formal language syntax and semantics, phrase structure grammars, and the Chomsky hierarchy. You will learn how to classify languages and explore the concepts of ambiguity in context-free grammar and its implications. In particular, you will learn about the compilation process including lexical analysis and syntactic analysis, recursive descent parsers and semantic analysis. Finally, you get to investigate the synthesis phase, where interme

  • Machine LearningOptional
    Module details

    Delve into machine learning, a fundamental concept in artificial intelligence that enables a computer to learn how to perform a task from data rather than traditional programming. In this module, you will study the key ideas and techniques behind machine learning and develop the practical skills needed to understand the implications and potential of machine learning in business and society. You will begin by looking at real-world problems, challenges, and current machine learning methodology. Building on this, you will cover a variety of approaches to machine learning, from decision trees to a wide range of deep neural networks, including multilayer perceptrons, convolutional neural networks

  • Natural Language ProcessingOptional
    Module details

    Gain a broad understanding of Natural Language Processing (NLP), a branch of artificial intelligence where computational methods are used to analyse and understand human languages. Throughout the module, you will be exposed to the core concepts surrounding the NLP pipeline, covering methods and techniques for data collection, cleaning, tokenisation, and annotation using a hierarchy of linguistic levels (e.g. morphology, syntax, and semantics). You will experiment with and comparatively evaluate different methods and techniques, including rule-based, probabilistic, machine learning and deep learning approaches. You will also learn to apply and adapt NLP pipelines and tools to real-world text

  • Quantum ComputingOptional
    Module details

    We introduce you to quantum computing's core principles and applications, contrasting its capabilities with classical systems. You will master Dirac notation and essential linear algebra, before examining quantum mechanics' four postulates, including qubits, gates, and circuit models. You will cover fundamental algorithms, including Deutsch's algorithm (implemented via Qiskit), Simon's problem, Bernstein-Vazirani, Grover's search (with BBBV Theorem analysis), and Shor's factorisation algorithm's impact on RSA cryptography. Quantum cryptography components address post-quantum security and QKD protocols, while quantum information theory explores superdense coding, the no-cloning theorem and te

  • Secure Artificial IntelligenceOptional
    Module details

    Artificial Intelligence (AI) is being rapidly adopted in both research and industry, via technologies such as generative AI and large language models (LLM). They are being used for a range of applications by enhancing cyber security through the detection of anomalies, identifying threats, and monitoring abnormal activities. However, AI itself is susceptible to various attacks, such as prompt injection, data leakages, jailbreaking, bypassing guardrails, model backdoors, and more. In this module, you will learn the fundamentals of AI for security and security for AI. This encompasses both how AI can be leveraged to augment and improve established cyber security techniques (from firewalls, risk

  • Secure Cyber Physical SystemsOptional
    Module details

    Understand security threats to cyber physical systems (CPS), such as industrial control systems, Internet of Things and connected vehicles, as well as techniques to mitigate these threats. Compared to traditional computer systems, CPS have limited resources and are typically deployed into a physical environment. This impacts the implementation of security techniques, as due to the environment they are deployed in you must consider both digital and physical attacks. This module introduces how to identify the appropriate security techniques to use for a CPS. You will come to understand how to write secure applications for CPS and which alternative mitigations are appropriate. You will also lea

  • Secure Distributed SystemsOptional
    Module details

    Distributed systems are the foundation upon which modern large-scale infrastructures are built, such as Cloud and service-oriented architectures (also known as ‘as a service’). You’ll investigate the cryptographic techniques used to build such systems, and secure distributed systems themselves. You’ll study the design approaches to constructing a secure distributed system, including the common vulnerabilities and attack surfaces associated with distributed systems, and the widely adopted design patterns used to mitigate them. To ensure the correctness of such systems, you will be introduced to formal verification techniques covering system specification and the verification of their correctn

Source: provider course page. Modules can change; required/optional status, credits, descriptions and assessment are shown only when explicitly published.

Course in depth

What this course covers, who it suits and where it leads.

What you'll study

This integrated master's combines computer science fundamentals with a substantial work placement. You'll typically begin with programming in Python and Java, computer systems architecture, and discrete mathematics. Year 2 moves to algorithms, data structures, databases and software engineering, alongside artificial intelligence and machine learning. Year 3 introduces specialist options such as artificial intelligence, cybersecurity, data science, software engineering, systems and networks, or human-computer interaction. You'll complete a major individual project, and throughout the course gain professional experience alongside or embedded within your studies. A course like this normally progresses from core technical foundations to specialised depth, culminating in both applied research and real-world workplace capability.

Who it's for

This course suits students with A-level qualifications or equivalent. Most accepted students held A-levels, and the typical UCAS tariff band among recent entrants was 144–159 points. You'll need to be comfortable with full-time study over four years. Check the university's funding pages for bursaries and scholarships.

Careers & job market

Across Computer Science courses nationally, 85% of graduates are in work or further study 15 months after graduating. Of those working, 75% are in highly skilled roles or continuing their studies. National earnings data shows starting salaries typically fall between £25,000 and £35,000 at 15 months post-graduation, rising to £29,750–£42,000 after five years. These figures reflect national outcomes; your own trajectory will depend on your choices, experience, and the opportunities you pursue.

University & format

This MSci (Hons) is studied full-time over 4 years at Lancaster University, a public university founded in 1964, based at Bailrigg Campus in Lancaster. Taught in English, the course is delivered by a nationally recognised UK degree-awarding body and carries Silver accreditation from the Office for Students' Teaching Excellence Framework (2023). The UCAS code is G404.

Student satisfaction

How students on this course answered the National Student Survey, by theme.

The teaching on my course
68%
Learning opportunities
66%
Assessment and feedback
56%
Academic Support
85%
Organisation and management
48%
Learning resources
93%
Student voice
67%

Share of students responding positively.

Published threshold met NSS publication requires sufficient responses; small differences are not a rank. NSS mean of 7 published themes (Discover Uni snapshot 2026-06-21)

Applicant information

The next application dates for this course, followed by facts the provider publishes.

Application timelineWhat happens next
  1. 2027 entryCompleted applications can be submitted

    Your application needs a reference before you can send it.

  2. 2026 entryFinal date for 2026 applications

    Applications must reach UCAS by 18:00 UK time.

  3. 2026 entryLast day to add a Clearing choice

    Check that this course still has a vacancy before adding it.

  4. 2027 entryEqual-consideration deadline

    18:00 UK time for most undergraduate courses.

Show 5 later dates
  1. 2027 entryUCAS Extra opens

    Applicants who used all five choices and hold no offer may be able to add another choice.

  2. 2027 entryLast day applications go directly to providers

    Applications received after 18:00 UK time are entered into Clearing.

  3. 2027 entryClearing opens

    Eligible applicants can see vacancies and release themselves into Clearing.

  4. 2027 entryFinal date for 2027 applications

    Applications must reach UCAS by 18:00 UK time.

  5. 2027 entryLast day to add a Clearing choice

    Check that this course still has a vacancy before adding it.

Published entryAAA typical offer

Provider-published requirement; check the linked course page before applying.

PlacementPublished placement option

Work placement. Availability, selection and pay can vary.

Open daysOpen days and tours

See and book current events. Dates can fill or change.

Entry & how to get in

Typical offer (from the provider)The university’s course page lists a typical A-level offer of AAA. Always check the provider for the current offer and subject requirements.
Most entrants held A-levels or equivalent95% of accepted students came in with A-levels or equivalent (entrants over recent years).
Typical UCAS tariff: 144 - 159 pointsThe most common UCAS tariff band among accepted students. This is what entrants had, not a stated requirement.
Entry requirements are set by the universityGrades, subjects and contextual offers vary. Check Lancaster University's official course page for the current offer.

Who gets in

What recently admitted students actually held, official admissions data, not a stated requirement.

UCAS tariff of entrants

Grades are the A-level equivalent of each points band. Tap a band to check your own chances below.

Qualifications held on entry

QualificationShare
A-levels or equivalent95%
another higher-education qualification5%
a Baccalaureate5%

Entry & your chances

An honest read from the official entry data, plus your personal match.

Competitive entry

Accepted students typically held strong UCAS tariffs. Check how your predicted grades compare and whether a contextual offer applies.

Will you get in? Plot your grades

Pick your predicted A-levels and watch your UCAS points land on the real spread of students admitted to this course.

Each bar is the share of admitted students in that UCAS-points band (lower → higher). Grades show the A-level equivalent.

Add your grades to see where you land

Your points will drop onto the distribution above, with an honest above / within / below read.

Based on the official admitted-student tariff distribution. Many universities make contextual (reduced-grade) offers, so a result below the range doesn’t rule you out.

How to apply

Undergraduate applications go through UCAS. Here’s what matters for this course, the right deadline, the grades to aim for, and the steps in order.

Apply by13 January 2027, 18:00 UK timefor this course
Typical gradesA*AAA-level equivalent admitted students held
UCAS codeG404quote this on your application
  1. 1
    Register on UCAS Hub

    Create your UCAS application and add this course (code G404). One application covers up to five choices.

  2. 2
    Write your personal statement

    A single statement covers all your choices, so keep it broad enough for similar courses while showing genuine interest in this subject.

  3. 3
    Submit by 13 January 2027, 18:00 UK time

    UCAS equal-consideration deadline for most undergraduate courses. Source: UCAS 2027 dates.

  4. 4
    Reply to your offers

    When decisions are in, pick a firm (first) choice and an insurance (back-up) choice with slightly lower grades.

  5. 5
    Results day & confirmation

    On results day (mid-August) your place is confirmed if you meet the offer. Just missed? Talk to the university, or find a place through Clearing.

💡 Many universities make a contextual (reduced-grade) offer, for example based on your school’s results, time in care, or where you live. Ask Lancaster University whether you’re eligible before you apply; it can lower the grades you need.

Fees & funding

What this course costs and how UK student finance covers it.

Tuition per year

Homeup to £9,790 / yr
International£33,676 / yr

Provider fee page (England 2026/27 cap where not stated).

Check fees at Lancaster University →

For students who normally live in England

illustrative Maintenance Loan per year
£9,790tuition used per year, illustrative full-time England fee-cap scenario
illustrative borrowing over 4 years

2026/27 Student Finance England figures. Maintenance support is means-tested and this two-point view is not an entitlement calculator. The course total uses its published length and home fee where both are available; a missing full-time fee uses the clearly labelled England-cap scenario, while part-time fees and unknown lengths are never guessed. Use the official calculator. Scotland, Wales and Northern Ireland use separate systems: SAAS, Student Finance Wales, and Student Finance NI.

Starting on or after 1 January 2027?

The Lifelong Learning Entitlement is a separate system. A new learner’s tuition entitlement is currently stated as £39,160 (about 480 credits at 2026/27 fee levels), subject to prior study and eligibility. Check the official LLE guide.

Paying for it

  • Tuition Fee Loan: can cover eligible tuition up to the applicable limit and is paid straight to the provider.
  • Maintenance Loan: up to £10,830/yr away from home outside London (England, 2026/27), means-tested on household income.
  • Repayment: 9% of income above £25,000, nothing below it; written off after 40 years.
  • Earn alongside: most students work part-time in term, part-time roles on the StudySmarter job board.

England figures shown; Scotland, Wales & NI run their own schemes, check gov.uk.

Funding matched to this course

Scholarships & bursaries you could qualify for

All Lancaster University funding →
No verified named award is shown for this provider yet.

That does not mean no funding exists. Check the university directory for current amounts, eligibility and application dates.

We only display a named award when its provider source identifies the award and who it is for.

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Career quizApplication walkthroughSalary & CV check

Careers & earnings

What Computer Science graduates actually earn, from real outcome data, 15 months, 3 years and 5 years after graduating.

Graduate earnings: this course

WhenMedianTypical rangeGraduates
15 months after£33,500£30,000 – £39,50040
3 years after£35,000£27,000 – £42,500110
5 years after£45,500£33,500 – £63,000110

Nominal earnings for graduates of this course/subject at this provider. Moderate evidence. Published sample: 40; avoid reading small differences as meaningful. Cohort 2021-23.

Graduate outcomes, 15 months on: this course

90%
in work or further study 15 months on
90%
in highly skilled work or study
95%
continue past their first year
85%
find their work meaningful
90%
say work fits their future plans
  1. 1Graduate / Junior DeveloperFirst engineering role · 0–2 yrs
  2. 2Software EngineerShipping features end-to-end · 2–5 yrs
  3. 3Senior / Lead EngineerOwning systems and mentoring · 5–9 yrs
  4. 4Principal / Engineering ManagerArchitecture or leading teams · 9+ yrs

How pay grows: this course vs Computer Science nationally

Starting (15 months) HESA GO
£33,500
£25,000 – £35,000
After 3 years LEO
£35,000
£23,375 – £33,000
After 5 years LEO
£45,500
£29,750 – £42,000
national rangethis course’s medianaxis £21,500 – £47,500

National figures for Computer Science graduates, HESA Graduate Outcomes (15 months) and the Longitudinal Education Outcomes (LEO) dataset (3 & 5 years). These are national, not university-specific; actual pay varies by employer, region, role and experience. Different cohorts, so the bars are not one group over time.

Work out your pay

Headline figures hide a lot. Calculate realistic take-home pay for this field by role, region and experience, then check your CV before you apply.

What happened to 100 students?

Choose an outcome to translate the published percentage into a simple 100-person view. Each dot represents one percentage point, not an individual tracked student.

90 of 100

were in work or further study

15 months after graduation

75% working15% working and studying0% in further study90% in highly skilled work or study

Source: Discover Uni, using Graduate Outcomes and continuation data. Cohorts: 2022-23. Moderate evidence. Published sample: 40; avoid reading small differences as meaningful. Cohort 2021-23. Each tab is a separate published measure; categories can overlap and should not be added together.

Value compared with similar courses

How this course’s 5-year median earnings compare with Computer Science courses at the same study level.

This course £45,500Peer median £34,500Middle 50% £29,000–£43,000
80th percentile

Compared with 1,820 courses with compatible official earnings data. This is a course-value comparison, not a quality ranking.

UK occupations graduates enter

Published graduate destinations, joined conservatively to UK SOC 2020, ONS pay and Skills England demand.

  • Information Technology ProfessionalsSOC 2020 213 · 85% of published destinations · ASHE median £55,357

Discover Uni JOBLIST/JOBTYPE; ONS ASHE 2025 provisional, all employee jobs; Skills England Occupations in Demand 2025. SOC is shown only for an exact normalised label match; demand is shown only at exact four-digit SOC. Published sample: 35; response rate: 70%. Pay describes the occupation across workers, not a guaranteed graduate salary.

Job market & outlook

How Computer Science graduates fare in the labour market, and how AI is reshaping the work.

85%
in work or further study 15 months after graduating, across Computer Science courses nationally.
Graduate Outcomes
75%
of working graduates are in highly skilled work or further study.
highly skilled
85%
of students continue past their first year (still enrolled or completed).
continuation

How AI is changing the work

AI doesn't replace the profession, it shifts it: routine tasks get automated, while judgement, working with people and using AI well become more valuable.

What AI takes off your plate

  • Boilerplate and scaffolding code
  • First-pass tests and docs
  • Routine debugging and refactors
  • Standard data wrangling

More human than ever

  • System design and architecture trade-offs
  • Reviewing and owning correctness & security
  • Translating fuzzy problems into software
  • Leading delivery and mentoring

The strongest graduates pair subject depth with the ability to use AI tools critically.

Roles & employers

Where Computer Science graduates typically go, indicative destinations from graduate career data. Each role links to live openings on the StudySmarter job board.

Where they work

  • Tech companies
  • Banks & fintech
  • Consultancies
  • Government (GDS) & startups

Is this course right for you?

The essentials UK applicants ask about: finance, outcomes, entry and quality.

💷

Student finance

For comparison, the standard full-time England tuition cap is up to £9,790 per year in 2026/27; the actual fee varies by course and provider. If you normally live in England, eligible students can apply for a Tuition Fee Loan, plus a Maintenance Loan for living costs. Under Plan 5 you repay 9% of income above £25,000, nothing below that, and the balance is written off after 40 years.

📈

Where graduates go

90% were in work or further study 15 months after graduating, with a median salary of £33,500. See the full breakdown in Careers & earnings above.

🎯

Your entry chances

Use the UCAS points calculator above to see how your predicted grades compare with admitted students, and whether a contextual offer could apply.

Official-data snapshot

Averaging the official measures published for it, this course scores 8.5 out of 10: NSS 69% · in work or study 90% · continued 95%.

Who studies here and in this subject?

Provider- and UK subject-level context.

The University of Lancaster

All students18,620
International22.4%
Aged 25+16.7%

Computing across the UK

Students205,990
Aged 25+31.2%

HESA student record 2024/25. Counts are rounded.

Local crime-data context

A neutral snapshot around the published teaching location.

Around Bailrigg Campus, Lancaster

28 street-level reports returned within roughly one mile across 2026-04 to 2026-06.

Other Theft 9Violent Crime 4Bicycle Theft 3Anti Social Behaviour 2Burglary 2

Police.uk street-level API. Approximate locations, not confined to campus. England, Wales and Northern Ireland; not Scotland.

Is Computer Science right for you?

Tick what applies to you and see how good a fit it is.

International students

What applying to Lancaster University from outside the UK involves: fees, English, visa, funding and living costs.

Tuition fees

International tuition is £33,676 / year for this course (from the provider’s fee page). You’re not eligible for UK Tuition Fee or Maintenance Loans, so plan for fees plus living costs upfront.

English language

Most UK undergraduate courses ask for around IELTS 6.0–6.5 (no band below 5.5–6.0), or an accepted equivalent. If you’re just short, most universities run a pre-sessional English course that counts towards the requirement.

Student visa

You’ll usually need a Student visa (Student Route). After you accept an offer the university issues a CAS; you then show funds for fees plus about £1,023–£1,334/month living costs and pay the Immigration Health Surcharge for NHS access.

Scholarships & funding

Many universities offer international/global scholarships (often £2,000–£6,000/yr), check Lancaster University’s funding pages.

Living costs

Budget roughly £1,100–£1,400/month outside London and £1,400–£1,800/month in London for rent, food and travel; the figure also matters for your visa.

Working while you study

A Student visa usually allows up to 20 hours/week in term time and full-time in holidays, useful alongside study, though not something to rely on for fees.

Visa rules and fees change. Always confirm the current requirements with Lancaster University and gov.uk before you apply.

Common questions

Entry is competitive. Accepted students typically held strong UCAS tariffs. The most common tariff band among recent entrants was 144 - 159 UCAS points. Use the calculator on this page to see where your predicted grades would put you; many universities also make lower contextual offers.
Set by Lancaster University. Most accepted students held A-levels or equivalent. Check the university's course page for the exact offer.
For Computer science graduates from this provider, 90% were in work or further study 15 months after graduating, 90% in highly skilled roles, typical earnings around £33,500. (HESA Graduate Outcomes / LEO, via Discover Uni.)
For comparison, the standard full-time England tuition cap is up to £9,790 per year in 2026/27; the actual fee varies by course and provider. If you normally live in England, eligible students can apply for a Tuition Fee Loan, plus a Maintenance Loan for living costs. Under Plan 5 you repay 9% of income above £25,000, nothing below that, and the balance is written off after 40 years. See Fees & funding on this page to work out your numbers.
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